Despite the remarkable success of highly active antiretroviral therapy (HAART), prolonged administration of antiietroviral agents is commonly associated with the emergence of resistant viruses and subsequent treatment failure. In response to the need for additional antiretroviral agents with non-overlapping resistance profiles, the first entry inhibitor (Fuzeon) received regulatory approval in 2004 and a growing number of candidates are currently in clinical development. As with protease and reverse transcriptase inhibitors, both the development and use of entry inhibitors will benefit from the comprehensive appreciation of the phenotypic and genotypic profiles of drug resistant variants. In this regard, large databases populated with routine drug resistance test results have been extremely useful in defining accurate phenotypic correlates and genotypic determinants of antiretroviral drug resistance. The overall goal of this SBIR program is to create, populate and exploit an HIV-1 envelope database comprised of high quality data derived from genotypic and phenotypic assays recently developed at ViroLogic to characterize and evaluate entry inhibitors and vaccines. The unique value of proposed database derives from the fact that each env genotype will be associated with phenotypic data comprised of (1) co-receptor tropism, (2) entry inhibitor susceptibility, and/or (3) neutralizing antibody sensitivity. The inter- and intra-patient heterogeneity of the HIV-1 envelope (env) gene presents significant analytical challenges that do not similarly complicate the analysis of the more conserved polymerase (pol) gene encoding protease and reverse transcriptase. Consequently, the establishment of a comprehensive env database containing reliable and informative genotypic data will require innovative analytical solutions. This application describes the development of computational resources that will be necessary to expand and leverage a unique database of phenotypically characterized, full-length HIV-1 env sequences derived from a large and diverse collection of clinical samples. More specifically, we will create and evaluate novel methods to efficiently compile HIV-1 envelope genotypes, standardize envelope genotype reporting, and correlate genetic determinants with phenotype. Once established, this env database and associated computational tools will be used to create and enhance a flexible portfolio of informational products with diverse applications, including patient management, new drug/vaccine discovery and development, and market research.